WO2023036243A1 - Dispositifs médicaux, procédés et systèmes de surveillance des dispositifs médicaux - Google Patents

Dispositifs médicaux, procédés et systèmes de surveillance des dispositifs médicaux Download PDF

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Publication number
WO2023036243A1
WO2023036243A1 PCT/CN2022/117823 CN2022117823W WO2023036243A1 WO 2023036243 A1 WO2023036243 A1 WO 2023036243A1 CN 2022117823 W CN2022117823 W CN 2022117823W WO 2023036243 A1 WO2023036243 A1 WO 2023036243A1
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WIPO (PCT)
Prior art keywords
medical device
information
scanning
examination table
images
Prior art date
Application number
PCT/CN2022/117823
Other languages
English (en)
Inventor
Shujie SONG
Die LI
Changwei YANG
Original Assignee
Shanghai United Imaging Healthcare Co., Ltd.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from CN202111052132.5A external-priority patent/CN113647967A/zh
Priority claimed from CN202111087938.8A external-priority patent/CN113796875A/zh
Application filed by Shanghai United Imaging Healthcare Co., Ltd. filed Critical Shanghai United Imaging Healthcare Co., Ltd.
Priority to EP22866704.4A priority Critical patent/EP4329618A1/fr
Publication of WO2023036243A1 publication Critical patent/WO2023036243A1/fr

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/02—Arrangements for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis
    • A61B6/03—Computed tomography [CT]
    • A61B6/032—Transmission computed tomography [CT]
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/02—Arrangements for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis
    • A61B6/03—Computed tomography [CT]
    • A61B6/037—Emission tomography
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/04—Positioning of patients; Tiltable beds or the like
    • A61B6/0407—Supports, e.g. tables or beds, for the body or parts of the body
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/04—Positioning of patients; Tiltable beds or the like
    • A61B6/0487—Motor-assisted positioning

Definitions

  • the present disclosure relates to the field of medical apparatus and instruments, in particular, to a medical device, a method and a system for monitoring the medical device.
  • a medical device for scanning In the process of treatment and diagnosis for a patient via a medical device, a medical device for scanning is usually required to scan the patient to obtain relevant information of a nidus.
  • an operator e.g., a medical staff
  • keys of the medical device often get stuck in the process of using the medical device, or other abnormal conditions caused by an unexpected motion of the medical device may occur when there is no operator.
  • the process of scanning not only the working intensity of the operator is high, but also the scanning efficiency is low.
  • One aspect of the present disclosure may provide a method for monitoring a medical device.
  • the method may include: obtaining a plurality of first images of a scanning room acquired by a first monitoring device arranged in the scanning room; obtaining an analysis result by analyzing the plurality of first images; and controlling the medical device based on the analysis result, the medical device including an examination table; wherein a control mode of the medical device may include at least one of controlling the medical device to adjust a height of the examination table, controlling the medical device to send an object to a target position, or controlling a running state of the medical device.
  • the medical device may include: a scanner configured to perform a medical scan to obtain scanning data of a target position of an object; an image acquisition device configured to obtain a plurality of first images of a scanning room; a processor configured to obtain an analysis result by analyzing the plurality of first images and determine a control mode of the medical device based on the analysis result; and a control mechanism configured to control the medical device based on the control mode.
  • the system may include: an acquisition module configured to obtain a plurality of first images of a scanning room acquired by a first monitoring device arranged in the scanning room; an image analysis module configured to obtain an analysis result by analyzing the plurality of first images; and a control module configured to control the medical device based on the analysis result, the medical device including an examination table, wherein a control mode of the medical device includes at least one of controlling the medical device to adjust a height of the examination table, controlling the medical device to send an object to a target position, or controlling a running state of the medical device.
  • the device may include at least one processor and at least one memory, wherein the at least one memory is configured to store executable instructions, and the at least one processor is configured to perform a method in above embodiments when executing at least a portion of the executable instructions.
  • Another aspect of the present disclosure may provide a non-transitory computer readable medium that stores executable instructions, wherein when the executable instructions are read by at a computing device, the computing device performs a method in above embodiments.
  • FIG. 1 is a schematic diagram illustrating an application scenario of an exemplary method for monitoring a medical device according to some embodiments of the present disclosure
  • FIG. 2 is a schematic diagram illustrating an exemplary software and/or hardware of a computing device according to some embodiments of the present disclosure
  • FIG. 3 is a schematic diagram illustrating an exemplary software and/or hardware of a terminal device according to some embodiments of the present disclosure
  • FIG. 4 is a block diagram illustrating an exemplary processing device for monitoring a medical device according to some embodiments of the present disclosure
  • FIG. 5 is a flowchart illustrating an exemplary process for monitoring a medical device according to some embodiments of the present disclosure
  • FIG. 6 is a flowchart illustrating an exemplary process for controlling a medical device according to some embodiments of the present disclosure
  • FIG. 7 is a schematic diagram illustrating an exemplary arrangement of structures of a medical device according to some embodiments of the present disclosure.
  • FIG. 8 is a flowchart illustrating an exemplary process for monitoring a running state of a medical device according to some embodiments of the present disclosure
  • FIG. 9 is a flowchart illustrating an exemplary process for obtaining expected running information of a medical device according to some embodiments of the present disclosure.
  • FIG. 10 is a schematic diagram illustrating an exemplary system for monitoring a medical device according to some embodiments of the present disclosure.
  • system, ” “device, ” “unit, ” and/or “module” used herein are one method to distinguish different components, elements, parts, sections, or components of different levels in ascending order. However, the terms may be displaced by other expressions if they may achieve the same purpose.
  • the flowcharts used in the present disclosure may illustrate operations executed by the system according to embodiments in the present disclosure. It should be understood that a previous operation or a subsequent operation of the flowcharts may not be accurately implemented in order. Conversely, various operations may be performed in inverted order, or simultaneously. Moreover, other operations may be added to the flowcharts, and one or more operations may be removed from the flowcharts.
  • a medical staff may need to operate an examination table of the medical device based on a height, a weight and other information of different patients, and adjust the height of the examination table to an appropriate height, which is convenient for patients to go to or get off the examination table.
  • the medical stuff may also need to guide the patient to adjust a position, to ensure that a scanned image contains information of a target position of the patient.
  • the workload of the medical staff may be increased, and the scanning efficiency may be reduced.
  • various abnormal conditions may occur, such as abnormal motion of the medical device, mistakenly touching from the patient, key being stuck, etc., which may cause potential harm to the patient, and affect the scanning efficiency.
  • Some embodiments of the present disclosure provide a medical device and a method for monitoring the medical device.
  • a plurality of images of a medical device and/or an object may be obtained by at least one monitoring device in a scanning room. Based on an analysis result of the plurality of images, a height of an examination table of the medical device may be controlled and a running state of the medical device may be monitored. Thus, the time of the scanning may be reduce, and the scanning may be rapidly performed.
  • FIG. 1 is a schematic diagram illustrating an application scenario of an exemplary system for monitoring a medical device according to some embodiments of the present disclosure.
  • a monitoring system 100 may include a medical device 110 (e.g., a CT scanner shown in FIG. 1) , a network 120, a terminal 130, a processing device 140, a storage device 150, and a monitoring device 160.
  • the components in the monitoring system 100 may be connected with each other in various ways.
  • the medical device 110 may be connected with the processing device 140 via the network 120.
  • the medical device 110 may be directly connected with the processing device 140 (as shown by the two-way arrow in the dotted line connecting the medical device 110 and the processing device 140) .
  • the storage device 150 may be connected with the processing device 140 directly or via the network 120.
  • the monitoring device 160 may be connected with the processing device 140 via the network 120.
  • the terminal 130 may be directly connected with the processing device 140 (as indicated by the two-way arrow in the dotted line connecting the terminal 130 and the processing device 140) or connected with the processing device 140 via the network 120.
  • the medical device 110 may scan an object and/or generate a plurality of data about the object.
  • the object may also be referred to as a scanning object, a target object, a target, or a detected object, and the above terms may be used interchangeably.
  • the object may be a creature, such as a patient, an animal, or the like.
  • the object may be placed on an examination table 116.
  • the object may move with the examination table 116 along a transverse direction (e.g., the x-axis direction in FIG. 7) , a longitudinal direction (e.g., the z-axis direction in FIG. 7) of the medical device 110, and may enter a scanning region 115.
  • the medical device 110 may perform an operation based on a scanning protocol, and a corresponding medical image of the object may be obtained.
  • the medical device 110 may include a single-mode scanning device and/or a multi-mode scanning device.
  • the single-mode scanning device may include, for example, a computed tomography (CT) device, a positron emission computed tomography (PET) scanning device, a magnetic resonance imaging (MRI) scanning device, an X-ray scanning device, etc.
  • CT computed tomography
  • PET positron emission computed tomography
  • MRI magnetic resonance imaging
  • X-ray scanning device etc.
  • the multi-mode scanning device may include, for example, an X-ray imaging-magnetic resonance imaging (X-ray MRI) scanning device, a positron emission tomography X-ray imaging (PET-X-ray) scanning device, a single photon emission computed tomography magnetic resonance imaging (SPECT-MRI) scanning device, a positron emission tomography computer tomography (PET-CT) scanning device, etc.
  • X-ray imaging-magnetic resonance imaging (X-ray MRI) scanning device a positron emission tomography X-ray imaging (PET-X-ray) scanning device, a single photon emission computed tomography magnetic resonance imaging (SPECT-MRI) scanning device, a positron emission tomography computer tomography (PET-CT) scanning device, etc.
  • SPECT-MRI single photon emission computed tomography magnetic resonance imaging
  • PET-CT positron emission tomography computer tomography
  • imaging mode may broadly refer to an imaging method or technology that collects, generates
  • the network 120 may include any suitable network that facilitates the exchange of information and/or data of the monitoring system 100.
  • one or more components of the monitoring system 100 e.g., the medical device 110, the terminal 130, the processing device 140, the storage device 150, or the monitoring device 160
  • the processing device 140 may obtain a medical image of the object from the medical device 110 via the network 120.
  • the network 120 may be any one or more of a wired or wireless network.
  • the network may be point-to-point, shared, central and other topologies or a combination of a plurality of topologies.
  • the network 120 may include one or more network access points.
  • network 120 may include wired or wireless network access points.
  • the terminal 130 may include a mobile device 130-1, a tablet computer 130-2, a notebook computer 130-3, or any combination thereof.
  • the terminal 130 may interact with other components in the monitoring system 100 via the network 120.
  • the terminal 130 may send one or more control instructions to the medical device 110 to control the examination table 116 to support the object into the scanning region 115.
  • the terminal 130 may also receive data such as medical images sent by the medical device 110.
  • the terminal 130 may receive information and/or instructions input by a user (e.g., a user of the medical device 110, such as a doctor) and send the received information and/or instructions to the medical device 110 or the processing device 140 via the network 120.
  • a doctor may input an operation instruction to the medical device 110 via the terminal 130.
  • the terminal 130 may be a portion of the processing device 140.
  • the terminal 130 and the processing device 140 may be integrated as a control device (e.g., a console 1020 shown in FIG. 10) of the medical device 110.
  • the terminal 130 may be omitted.
  • the processing device 140 may process data and/or information obtained from the medical device 110, the terminal 130, the storage device 150, and/or the monitoring device 160. For example, the processing device 140 may acquire a medical image of the object. For another example, the processing device 140 may determine posture information of the object based on a plurality of first images of the object collected by the monitoring device 160, and then adjust the height of the examination table 116. For example, the processing device 140 may determine actual positioning information of the object based on a plurality of second images of the object on the examination table acquired by the monitoring device 160. For another example, the processing device 140 may acquire a video of the medical device 110 based on the monitoring device 160, and determine the actual running information of the medical device 110 by analyzing the video, so as to determine whether the running state of the medical device 110 is abnormal.
  • the processing device 140 may be a single server or a group of servers. The group of servers may be centralized or distributed. In some embodiments, the processing device 140 may be local or remote. For example, the processing device 140 may access information and/or data stored in or acquired by the medical device 110, the terminal 130, and/or the storage device 150 via the network 120. For another example, the processing device 140 may be directly connected with the medical device 110, the terminal 130, the storage device 150, and/or the monitoring device 160 to access stored or acquired information and/or data. In some embodiments, the processing device 140 may be implemented on a cloud platform.
  • the cloud platform may include private cloud, public cloud, hybrid cloud, community cloud, distributed cloud, internal cloud, multi-cloud, or the like, or any combination thereof.
  • the processing device 140 may be implemented on a computing device 200 including one or more components shown in FIG. 4 in this specification.
  • the storage device 150 may store data and/or instructions.
  • the storage device 150 may store data obtained from the medical device 110, the terminal 130, and/or the processing device 140.
  • the storage device 150 may store motion information of the object designed in advance by a user (e.g., a doctor, an imaging technician) .
  • the storage device 150 may store data and/or instructions that the processing device 140 may execute or use to execute the exemplary methods described in the present disclosure.
  • the storage device 150 may store instructions of the processing device 140 to execute the methods shown in the flowcharts in the present disclosure.
  • the storage device 150 may include a mass storage device, a removable storage device, a volatile read-write memory, a read-only memory (ROM) , etc., or any combination thereof. In some embodiments, the storage device 150 may be implemented on a cloud platform.
  • the storage device 150 may be connected with the network 120 to communicate with one or more components of the monitoring system 100 (e.g., the medical device 110, the terminal 130, the processing device 140, the monitoring device 160, etc. ) .
  • One or more components of the monitoring system 100 may access data or instructions stored in the storage device 150 via the network 120.
  • the storage device 150 may be directly connected with or communicate with one or more components of the monitoring system 100 (e.g., the medical device 110, the terminal 130, the processing device 140, the monitoring device 160, etc. ) .
  • the storage device 150 may be a portion of the processing device 140.
  • the monitoring device 160 may be configured to collect images in a scanning room (e.g., a scanning room 101 shown in FIG. 7 or FIG. 10) . In some embodiments, the monitoring device 160 may be configured to collect a plurality of first images when the object enters the scanning room. In some embodiments, the monitoring device 160 may be configured to acquire a plurality of second images of the object on the examination table 116. In some embodiments, the monitoring device 160 may be configured to acquire a plurality of third images of the object. In some embodiments, the monitoring device 160 may be configured to acquire key control information of the medical device 110. In some embodiments, the monitoring device 160 may be configured to obtain running state information of the medical device 110. In some embodiments, the monitoring device 160 may be configured to obtain current operation information of the medical device 110.
  • a scanning room e.g., a scanning room 101 shown in FIG. 7 or FIG. 10
  • the monitoring device 160 may be configured to collect a plurality of first images when the object enters the scanning room. In some embodiments, the monitoring device
  • the monitoring device 160 may be configured to acquire image information of the object and image information of the medical device, respectively. For example, the monitoring device 160 may first acquire the first image and the second image of the object, and then acquire the current operation information of the medical device 110. As another example, the monitoring device 160 may first acquire the first image of the object, then acquire the current operation information of the medical device 110, and finally acquire the second image of the object. In some embodiments, the monitoring device 160 may be configured to simultaneously acquire image information of the object and image information of the medical device. For example, the monitoring device 160 may be configured to simultaneously acquire the second image of the object and the key control information of the medical device 110. In some embodiments, the monitoring device 160 may be configured to acquire image information of the object and/or image information of the medical device 110 in real time or at specific intervals.
  • the monitoring device 160 may be an image acquisition device.
  • the image acquisition device may be a three-dimensional (3D) camera, such as a TOF (time of flight) camera, a structured light camera, a binocular camera, a lidar camera, or the like, or a combination thereof.
  • the 3D camera may restore the 3D image of the object by determining the position and depth information of the object.
  • the image acquisition device may be equipped with an infrared camera device. At this time, the obtained image of the object may be an infrared image.
  • the infrared camera device may recognize the posture of the object through a surface temperature of the body of the object. Compared with the optical camera device, the infrared camera device may be weakly affected by a shooting background, shooting light and other factors, thus the accuracy of the infrared camera device may be higher.
  • the monitoring device 160 may be configured to acquire video/images in the scanning room.
  • the monitoring device 160 may include a first monitoring device 160-1 arranged in the scanning room 101, which may be configured to obtain the video/images of the object entering the scanning room. And the monitoring device 160 may also be configured to obtain the image of the running state of the medical device 110 in the scanning room.
  • the monitoring device 160 may be configured to acquire video/images in an operation room.
  • the monitoring device 160 may include a second monitoring device 160-2 arranged in an operation room 102, which may obtain a key operation image of an operator in the operation room 102, etc.
  • the monitoring device 160 may include a high-definition camera module of 720P, 1080P, 2K, 4K, etc.
  • the monitoring device 160 may include any type of camera, including but not limited to still camera, camera, high-speed camera, infrared camera, etc., which may not be limited herein.
  • the above description of the monitoring system 100 is merely for illustration, and does not limit the scope of application of the present disclosure.
  • the monitoring system 100 may include a displaying device.
  • components of the monitoring system 100 may have their own storage device, or may use a common storage device.
  • these modifications and changes may not deviate from the scope of the present disclosure.
  • FIG. 2 is a schematic diagram illustrating an exemplary software and/or hardware of a computing device according to some embodiments of the present disclosure.
  • a computing device 200 may include a processor 210, a memory 220, an input/output (I/O) 230, and a communication port 240.
  • the computing device 200 may be arranged in the processing device 140.
  • the processor 210 may execute computer instructions (e.g., program codes) and perform functions of the processing device 140 based on techniques described in the present disclosure.
  • the computer instructions may include routines, programs, objects, components, signals, data structures, procedures, modules, and functions that perform specific functions described herein.
  • the processor 210 may obtain motion data of the examination table of the medical device 110 or the scanning data of the medical device 110 from the storage device 150 and/or the terminal 130.
  • the processor 210 may include a microcontroller, a microprocessor, a reduced instruction set computer (RISC) , an application specific integrated circuit (ASIC) , an application specific instruction set processor (ASIP) , a central processing unit (CPU) , a graphics processor (GPU) , a physical operation processor (PPU) , a microcontroller unit, a digital signal processor (DSP) , a field programmable gate array (FPGA) , an advanced RISC machine (ARM) , a programmable logic device and any circuit or processor capable of performing one or more functions, or any combination thereof.
  • RISC reduced instruction set computer
  • ASIC application specific integrated circuit
  • ASIP application specific instruction set processor
  • CPU central processing unit
  • GPU graphics processor
  • PPU physical operation processor
  • DSP digital signal processor
  • FPGA field programmable gate array
  • ARM advanced RISC machine
  • the computing device 200 in the present disclosure may include a plurality of processors, so operations of the method performed by one processor described in the present disclosure may be performed by the plurality of processors jointly or separately.
  • operations A and B are performed by the processor of the computing device 200 in the present disclosure, it should be understood that the operations A and step B may also be performed jointly or separately by two different processors of the computing device 200 (e.g., a first processor performs the operation A, a second processor performs the operation B, or the first processor and second processor jointly perform the operations A and B) .
  • the processor 210 may receive instructions following a scanning protocol for imaging/scanning the object. For example, the processor 210 may instruct the examination table 116 of the medical device 110 to move the object into the scanning region 115. For another example, the processor 210 may send a motion termination instruction to the medical device 110 via a controller connected with the medical device 110. As another example, the processor 210 may also provide certain control signals to control a rotation speed and a position of a gantry in the scanning region 115. For another example, the processor 210 may also provide certain control signals to control the on-off of the tube in the scanning region 115. In some embodiments, the processor 210 may acquire scanning data (e.g., the medical image) of the object in the scanning region of the scanning device.
  • scanning data e.g., the medical image
  • the memory 220 may store data/information obtained from the medical device 110, the terminal 130, the storage device 150, or any other component of the monitoring system 100.
  • the memory 220 may store one or more programs and/or instructions to perform the methods described in the present disclosure.
  • the memory 220 may store a program for the processor 210 to perform a processing operation, and may also store posture information of the object determined by the processor 210 based on the acquired image data (e.g., the first image) .
  • the memory 220 may store relevant programs for controlling the examination table 116 to perform step motion or continuous motion based on a predetermined trajectory and a predetermined speed.
  • the memory 220 may store a predetermined correspondence between the operation instruction and the excepted operation information of the medical device.
  • the input/output (I/O) 230 may input or output signals, data, or information. In some embodiments, the input/output 230 may allow a user to interact with processor 210. In some embodiments, the input/output 230 may include an input device and an output device.
  • the input device may include a keyboard, a mouse, a touch screen, a microphone, a trackball, or the like, or any combination thereof.
  • the output device may include a displaying device, a speaker, a printer, a projector, or the like, or any combination thereof.
  • a user may input data related to an object (e.g., a patient) that is imaged/scanned by the input/output 230.
  • the data related to the object may include identity information (e.g., name, age, gender, medical history, contract information, physical examination results, etc. ) and/or include scanning protocol information.
  • the user i.e., the operator
  • the input/output 230 may also display a scanned image generated based on sampling data.
  • the communication port 240 may be connected with a network (e.g., the network 120) to facilitate data communication.
  • the communication port 240 may establish a connection between the processing device 140 and the medical device 110, the terminal 130, or the storage device 150.
  • the connection may be a wired connection, a wireless connection, or a combination thereof, which may allow transmission and reception of data.
  • the communication port 240 may be a standardized communication port, such as RS232, RS485, etc.
  • the communication port 240 may be a specially designed communication port.
  • the communication port 240 may be designed based on the digital imaging and communications in medicine (DICOM) protocol.
  • DICOM digital imaging and communications in medicine
  • computing device 200 is merely for illustration, and does not limit the scope of application of the present disclosure. It should be understood that for those skilled in the art, after understanding the principle of the system, any combination of various components may be made, or a subsystem may be formed to connect with other components without departing from this principle. For example, components may share a storage device, or each of the components may have its own storage device. These changes are within the scope of the present disclosure.
  • FIG. 3 is a schematic diagram illustrating an exemplary software and/or hardware of a terminal device according to some embodiments of the present disclosure.
  • a terminal device 300 may include one or more (only one is shown in FIG. 3) processors 320 (a processor 320 may include, but be not limited to, a microprocessor, e.g., a microcontroller unit (MCU) , or a programmable logic device, e.g., a field programmable gate array (FPGA) ) , and a memory 330 for storing data.
  • the terminal device 300 may also include a transmission device 310 for communication and an input/output device 340.
  • the terminal device 300 may be placed in the processing device 140 or the terminal 130. It should be understood by those skilled in the art that structures shown in FIG. 3 is merely for illustration, and does not limit the structures of the above terminal device 300.
  • the terminal device 300 may also include more or fewer components than shown in FIG. 3, or may have a different configuration from that shown in FIG. 3.
  • the memory 330 may be configured to store control programs, such as software programs and modules of application software, such as the control programs corresponding to method for monitoring a running state of medical device in some embodiments of the present disclosure.
  • the processor 320 may implement the method described in the embodiments of the present disclosure by execute a control program stored in the memory 330 to perform various applications and data processing operations.
  • the memory 330 may include a high-speed random access memory, a nonvolatile memory, or the like.
  • the nonvolatile memory may include one or more magnetic storage devices, flash memory, or other nonvolatile solid-state memories.
  • the memory 330 may further include memory remotely set relative to processor 320, which may be connected with terminal device 300 via a network. Examples of the network described above may include, but be not limited to, the Internet, intranet, local area network (LAN) , mobile communication network, or any combination thereof.
  • LAN local area network
  • the transmission device 310 may be configured to receive or transmit data via a network. Examples of the network described above may include a wireless network provided by a communication provider of the terminal device 300.
  • the transmission device 310 may include a network interface controller (NIC) , which may be connected with other network devices via a base station, to communicate with the Internet.
  • the transmission device 310 may be a radio frequency (RF) module for communicating with the Internet wirelessly.
  • NIC network interface controller
  • RF radio frequency
  • FIG. 4 is a block diagram illustrating an exemplary processing device for monitoring the medical device according to some embodiments of the present disclosure.
  • the processing device 400 as described in FIG. 4 may be an exemplary embodiment of the processing device 140 as described in FIG. 2.
  • the processing device 400 may also be referred to as an apparatus for monitoring the medical device (i.e., a monitoring apparatus) .
  • the processing device 400 may include an acquisition module 410, an image analysis module 420, and a control module 430.
  • the acquisition module 410 may be configured to obtain information such as a plurality of images, or a scanning protocol.
  • the acquisition module 410 may further include an image acquisition unit 412 and a scanning protocol acquisition unit 414.
  • the image acquisition unit 412 may be configured to acquire a plurality of first images in the scanning room by a first monitoring device arranged in the scanning room.
  • the plurality of first images may include an image of the object and/or a video of the medical device.
  • the image acquisition unit 412 may acquire a plurality of second images of the object on the examination table by the first monitoring device.
  • the image acquisition unit 412 may be configured to acquire a plurality of third images of the object.
  • the image acquisition unit 412 may be configured to acquire key control information of the medical device as current operation information based on the second monitoring device.
  • the scanning protocol acquisition unit 414 may automatically obtain a corresponding scanning protocol based on identity information of the object.
  • the scanning protocol may include at least predetermined positioning information, a reference rotation speed of a gantry of the medical device, one or more reference parameters associate with anode preheating of a tube of the medical device, and a reference positioning state of each component of the medical device.
  • the image analysis module 420 may be configured to obtain an analysis result by analyzing the plurality of images. In some embodiments, the image analysis module 420 may be configured to determine mental state information of the object based on the plurality of first images or the plurality of second images of the object, and determine whether the object is suitable for scanning based on the mental state information.
  • the image analysis module 420 may further include an identity information determination unit 422, a posture information determination unit 424, a positioning information determination unit 426, and a running information determination unit 428.
  • the identity information determination unit 422 may be configured to determine the identity information of the object based on the plurality of first images of the object. In some embodiments, the identity information determination unit 422 may be configured to determine the identity information of the object based on a mark set on the object.
  • the posture information determination unit 424 may be configured to determine the posture information of the object based on the plurality of first images of the object.
  • the positioning information determination unit 426 may be configured to determine actual positioning information of the object based on the plurality of second images.
  • the running information determination unit 428 may be configured to identify actual running information of the medical device based on the video of the medical device.
  • the actual running information may include image information and sound information.
  • the control module 430 may be configured to control the medical device based on the analysis result.
  • the control module 430 may further include an examination table control unit 432 and a running control unit 434.
  • the examination table control unit 432 may be configured to automatically adjust a height of the examination table of the medical device to a target height based on the posture information of the object. In some embodiments, the examination table control unit 432 may control the medical device to send the object to a target position for scanning when the actual positioning information of the object meet a predetermined condition by comparing the actual positioning information with the predetermined positioning information. In some embodiments, in response to determining that a scanning dose meets a requirement, the examination table control unit 432 may send the object to the target position for scanning. In some embodiments, after the scanning is completed, the examination table control unit 432 may control the examination table to adjust the height of the examination table to the target height. In some embodiments, the examination table control unit 432 may simulate a motion trajectory of the examination table from a position where the object goes to the examination table to the target position, and determine whether an interference involves between the object and the medical device.
  • the running control unit 434 may be configured to control the running state of the medical device based on the actual running information and the expected running information. In some embodiments, in response to determining that the medical device is in an abnormal state, the running control unit 434 may send a motion termination instruction to the medical device via the controller connected with the medical device and generate warning information.
  • control module 430 may adjust a rotation speed of a gantry of the medical device to a rotation speed in the scanning protocol, adjust one or more parameters associated with anode preheating of the tube of the medical device to the one or more reference parameters associate with anode preheating in the scanning protocol, and/or adjust a positioning state of each of the one or more components of the medical device to the reference positioning state in the scanning protocol.
  • control module 430 may generate warning information when an abnormal object exists in the scanning room and/or the object does not exist in the scanning room.
  • processing device 400 is merely for illustration, and is not intended to limit the scope of the present disclosure.
  • various modifications and changes may be made based on the present disclosure. However, these changes and modifications do not depart from the scope of the present disclosure.
  • one or more modules of the above processing device 400 may be omitted or integrated into a single module.
  • the processing device 400 may include one or more additional modules, such as a storage module for data storage.
  • FIG. 5 is a flowchart illustrating an exemplary process for monitoring a medical device according to some embodiments of the present disclosure.
  • process 500 may be performed by the monitoring system 100 or the processing device 400.
  • the monitoring method 500 for a medical device may be stored in a storage device (e.g., the storage device 150) in the form of a program or instruction, and the process 500 may be implemented when the monitoring system 100 (e.g., the processing device 140) executes the program or instruction.
  • the operations of 500 of the medical device presented below is illustrative.
  • process 500 may be implemented with one or more additional operations not described and/or one or more operations not discussed.
  • a sequence of operations in the process 500 shown in FIG. 5 and described below is not restrictive.
  • a plurality of images of a scanning room acquired by a first monitoring device arranged in the scanning room may be obtained.
  • operation 510 may be performed by the processing device 140, the computing device 200, the terminal device 300, or the processing device 400 (e.g., the acquisition module 410) .
  • the scanning room may refer to a room for accommodating the medical device, such as the scanning room 101 shown in FIG. 7 or FIG. 10.
  • the scanning room may be a room where the medical device (e.g., a CT scanning device, a PET scanning device, the MRI scanning device) is accommodated.
  • the medical device e.g., a CT scanning device, a PET scanning device, the MRI scanning device
  • the first monitoring device may include an image acquisition device for obtaining images.
  • the first monitoring device may include more than one image acquisition device that may be arranged in the scanning room.
  • the first monitoring device may include a plurality of image acquisition devices (e.g., 160-1 or 160-2 arranged in the scanning room 101.
  • the first monitoring device may include a plurality of image acquisition devices 160-1 arranged in the scanning room 101.
  • the plurality of images may include a plurality of images of an object and/or a plurality of images of the medical device.
  • one of the plurality of images may be a first image obtained by the first monitoring device when the object enters the scanning room, or may be a second image obtained by the first monitoring device when the object is on the examination table, or the like. More descriptions of the plurality of images related to the object may be found elsewhere in the present disclosure, for example, FIG. 6 and the descriptions thereof, which may not be described herein.
  • the plurality of images may be a video of the medical device, or monitoring images of a console obtained by the first monitoring device. More description of the plurality of images of the medical device may be found elsewhere in the present disclosure, for example, FIG. 8 and the descriptions thereof, which may not be described herein.
  • an analysis result may be obtained by analyzing the plurality of images.
  • operation 520 may be performed by the processing device 140, the computing device 200, the terminal device 300, or the processing device 400 (e.g., the image analysis module 420) .
  • analysis of the plurality of images may include the analysis of an image frame.
  • the processing device 140 may analyze a change of gray, a color distortion of the image frame, or the like.
  • the processing device 140 may extract a feature of the object (e.g., a pupil, a facial makeup, etc. ) in the frame image for analysis.
  • the analysis may include comparison or matching between the plurality of images, or the like.
  • the processing device may analyze an image using a trained image recognition model.
  • a trained image recognition model may include a face recognition model, an emotion recognition model, an expression recognition model, an image classification model, or the like, which may be configured to analyze the plurality of images.
  • the processing device may determine relevant information of the object and/or relevant information of the medical device by analyzing the plurality of images. For example, posture information and/or identity information of the object may be determined by analyzing a plurality of first images of the object. As another example, actual positioning information of the object may be determined by analyzing a plurality of second images of the object when the object is on the examination table. As still another example, mental state information of the object may be determined by analyzing a plurality of first images or a plurality of second images of the object. As a further example, actual running information of medical device may be determined by analyzing a video of medical device.
  • the medical device may be controlled based on the analysis results.
  • operation 530 may be performed by the processing device 140, the computing device 200, the terminal device 300, or the processing device 400 (e.g., the control module 430) .
  • the processing device may generate a corresponding control instruction or a control signal based on the analysis result and control the medical device according to the control instruction or the control signal.
  • the processing device may control the medical device to adjust a height of an examination table based on the analysis result.
  • the processing device 140 may adjust the height of the examination table 116 of the medical device 110 to a target height based on the posture information of the object. More description of adjusting the height of the examination table based on the posture information may be found elsewhere in the present disclosure, for example, FIG. 6 and the descriptions thereof, which may not be described herein.
  • the processing device may control the medical device to send the object to a target position based on the analysis result.
  • the processing device 140 may control the medical device 110 to send the object to the target position (e.g., the scanning region 115) for scanning in response to determining that the actual positioning information meets a predetermined condition by comparing the actual positioning information with predetermined positioning information. More description of the actual positioning information may be found elsewhere in the present disclosure, for example, FIG. 6 and the descriptions thereof, which may not be described herein.
  • the processing device may control the running state of the medical device based on the analysis result.
  • the processing device 140 may control the running state of the medical device 110 based on the actual running information and the excepted operation information of the medical device 110. More description of controlling the running state of medical device may be found elsewhere in the present disclosure, for example, FIG. 8 and FIG. 9 and the descriptions thereof, which may not be described herein.
  • whether an abnormal object exists in the scanning room may be determined based on a scanning scene and the plurality of images, and warning information may be generated in response to determining that the abnormal object exists in the scanning room.
  • the abnormal object may be a person unrelated to the scanning, such as a relative of the object, a bystander, a medical staff, or the like.
  • a person who needs to be in the scanning room may be different. For example, in the scene that the object needs help from the medical staff, the medical staff existing in the scanning room may not be warned, and in other scenes, the medical staff existing in the scanning room may be warned.
  • whether an abnormal object exists in the scanning room may be determined based on by determining a count of persons in the image. For example, the count of persons in the image of the scanning room may be identified, and based on the scanning scene, when the count of persons in the image is greater than a count of persons required in the current scanning scene, an abnormal object may exist in the scanning room.
  • whether an abnormal object exists in the scanning room may be determined by determining identity information of persons in the image. For example, identity information of each person contained in the image may be determined by an image recognition technique, and whether each person is a patient may be determined. When other person who are not patients or the only person in the image is not a patient, the abnormal object existing in the scanning room may be determined.
  • the warning information may include voice information, text information, video information, or the like.
  • the voice information reminding the abnormal object to leave may be played via a broadcasting device
  • the voice information may be “person who is not a patient, please leave as soon as possible! ”
  • the warning information may be displayed on a display screen.
  • whether the object is located in a predetermined region may be determined based on the plurality of images, and the warning information may be generated in response to determining that the object is not in the predetermined region.
  • the predetermined region may refer to a region where the object needs to be located.
  • the predetermined region may be determined based on different scenes. For example, three stages including before scanning, during scanning, and after scanning may correspond to different regions.
  • the predetermined region before scanning may be a position on the examination table. During scanning, the predetermined region may be the target region of the medical device. After scanning, the predetermined region may be a position next to the examination table.
  • the predetermined region information may be included in the scanning protocol.
  • position information of the object in the scanning room may be recognized based on the first image of the object to determine whether the object is located in a predetermined region. In some embodiments, the position information of the object in the scanning room may be recognized based on the second image of the object to determine whether the object is located in a predetermined region.
  • the warning information may include prompt information, movement information, or the like, in response to determining that the object is not in the predetermined region. For example, when the object is not in the predetermined region, a prompt tone may be emitted. As another example, when the object is not in the predetermined region, the object may be reminded to move a specific distance in a specific direction to reach the predetermined region.
  • the warning information may be output via broadcasting, displaying, or the like.
  • a sound may be used to prompt directly, for example, an alarm tone may be emitted.
  • control mode of the processing device to control the medical device may include, but be not limited to one or more control modes described above.
  • the above description of the process 500 is merely for illustration, and does not limit the scope of the present disclosure.
  • various modifications and changes may be made to the process 500 under the guidance of the present disclosure. However, these modifications and changes are still within the scope of the present disclosure.
  • FIG. 6 is a flowchart illustrating an exemplary process for controlling a medical device according to some embodiments of the present disclosure.
  • process 600 may be performed by the monitoring system 100 or the processing device 400.
  • the process 600 may be stored in a storage device (e.g., the storage device 150) in the form of programs or instructions, and the process 600 may be implemented when the monitoring system 100 (e.g., the processing device 140) executes the programs or the instructions.
  • the operations of the process 600 presented below is illustrative. In some embodiments, the process may be implemented with one or more additional operations not described and/or one or more operations not discussed. In addition, an order of the operations of the process 600 shown in FIG. 6 and described below may not intend to be restrictive.
  • a plurality of first images of the object acquired by a first monitoring device may be obtained.
  • operation 610 may be performed by an acquisition module 410 (e.g., the image acquisition unit 412) .
  • the first monitoring device (e.g., the monitoring device 160 shown in FIG. 1) may be an image acquisition device with a function of data acquisition, storage, and/or transmission.
  • the image acquisition unit 412 may communicate with the first monitoring device to acquire the plurality of first images of the object.
  • the first monitoring device may acquire the plurality of first images of the object 117 entering the scanning room 101.
  • the plurality of first images acquired by the first monitoring device may be a continuous video of the object entering the scanning room.
  • the image acquisition unit 412 may divide the continuous video into a plurality of still images, thus the plurality of first images may be acquired.
  • the plurality of still images i.e., the plurality of first images
  • a time interval between any two adjacent images of the plurality still images may be set to 1/24s (i.e., obtaining 24 frames of images with an equal time interval within 1 second) .
  • the time interval between any two adjacent images of the plurality of still images may be specifically set based on actual requirements.
  • the time interval may be specifically set as 1/25s, 1/48S, or 1/60swhich means that 25, 48, and 60 frames of images may be obtained with an equal time intervals within 1 second, respectively.
  • Setting the time interval for obtaining the plurality of still images may exclude some images with poor image quality (e.g., an overexposed image, or an image with afterimage) , thus the plurality of still images may maintain a high image quality, thus making the posture information extracted based on the images in subsequent operations more accurate.
  • image quality e.g., an overexposed image, or an image with afterimage
  • posture information of the object may be determined based on the plurality of first images of the object.
  • operation 620 may be performed by the image analysis module 420 (e.g., the posture information determination unit 424) .
  • the posture information determination unit 424 may perform operations such as gray-scale change, and/or color distortion on the plurality of first images of the object entering the scanning room acquired in operation 610, obtain contours of the object represented in the plurality of first images, and determine the posture information of the object based on a comparison between the contours and a predetermined contour.
  • the posture information determination unit 424 may determine feature points of the object based on the plurality of first images, and determine the posture information based on the feature points.
  • the posture information may include a sitting posture, a standing posture, a lying posture (e.g., a supine posture, a lateral posture) , or other postures.
  • coordinates of the feature points may be extracted from the plurality of first images using an algorithm, for example, OpenPose, Hourglass Network, Mask RCNN, or the like. Taking leg joints of the object as an example, the coordinates of each of the leg joints of the object (e.g., a knee joint, an ankle joint, a cross joint, etc. ) in each first image may be obtained based on at least one of the above algorithms.
  • feature point information of the body of the object may be obtained based on at least one of above algorithms.
  • the posture information determination unit 424 may determine whether the object is in a lying posture based on the feature point information of the body of the object. For example, when feature points of the body of the object are horizontally distributed or close to horizontally distributed, the object may be determined that the object is lying on the examination table.
  • the posture information determination unit 424 may determine whether the object is in a sitting posture (e.g., sitting in a wheelchair) or a standing posture based on the leg joints of the object. Specifically, the posture information determination unit 424 may connect the knee joint with the ankle joint by a line segment, and connect the knee joint with the cross joint by another line segment based on the coordinates of each joint of the leg joints, thus the posture information of the object may be determined based on an angle between the two line segments (the angle between the two line segments may be within 0° ⁇ 90°) .
  • the line segment between the knee joint and the ankle joint may be line segment A
  • the line segment between the knee joint and the cross joint may be line segment B.
  • a predetermined threshold e.g., the predetermined threshold is 45 °
  • the object may be considered to be in a sitting posture.
  • the angle between the line segment A and the line segment B is relatively small (e.g., close to 0°)
  • the object may be considered to be in a standing posture.
  • the coordinates of the feature points may have some noises.
  • the noises of the plurality of still images may include Gaussian noise, non-Gaussian noise, systematic noise, or the like, or any combination thereof.
  • the coordinates of the feature points may be de- noised to obtain de-noised coordinates of the feature points.
  • Kalman filtering may be used to filter the noise of a still image. Kalman filter is an algorithm that estimating a system state based on input and output observation data of the system by using a system state equation.
  • Kalman filtering may include a linear Kalman filtering, an extended Kalman filtering, a progressive extended Kalman filtering, an unscented Kalman filtering, or other filtering methods, or any combination thereof.
  • a scanning protocol corresponding to the object may be obtained.
  • the operation 630 may be performed by the acquisition module 410 (e.g., the scanning protocol acquisition unit 414) .
  • the scanning protocol may include information related to reference scanning parameters associated with scanning and/or reference reconstruction parameters associated with the scanning.
  • the reference scanning parameters may include a voltage (kV) of the tube, a current (mA) of the tube, a total exposure time, a scanning type (e.g., spiral scanning, axial scanning) , a field of view (FOV) , a pitch, a tilt angle of the gantry, a rotation time of the gantry, a slice thickness, or the like.
  • the reference image reconstruction parameters may include a reconstruction FOV, a reconstruction slice thickness, a reconstruction interval for image reconstruction, a window width (WW) , a window level (WL) , a reconstruction matrix, a reconstruction algorithm (e.g., a filtered back projection algorithm, a fan-beam reconstruction algorithm, an iterative reconstruction algorithm, etc. ) .
  • a reconstruction FOV a reconstruction FOV
  • WW window width
  • WL window level
  • a reconstruction matrix e.g., a filtered back projection algorithm, a fan-beam reconstruction algorithm, an iterative reconstruction algorithm, etc.
  • the scanning protocol may include predetermined positioning information.
  • the positioning information may reflect a region where the object is scanned and photographed.
  • the scanning protocol may include information such as a reference rotation speed of a gantry of the medical device, one or more reference parameters associated with anode preheating of a tube of the medical device, and a reference positioning state (e.g., a tilt angle of the gantry, a pitch, a FOV, etc. ) of each component of the medical device.
  • the scanning protocol acquisition unit 414 may obtain the scanning protocol corresponding to the object based on the identity information of the object.
  • the scanning protocol may be provided by an operator (e.g., a doctor or a technician) .
  • the identity information of the object may be determined based on the plurality of first images of the object. In some embodiments, the identity information of the object may be determined by a mark set on the object.
  • the identity information determination unit 422 may obtain a face image of the object based on the plurality of first images of the object, and then determine the identity information of the object based on the face image.
  • the object may be provided with a mark.
  • the mark may be set as a two-dimensional code, a wrist information code, radio frequency identification (RFID) , an integrated circuit (IC) card, or the like.
  • RFID radio frequency identification
  • IC integrated circuit
  • the object may present the mark (e.g., the wrist information code) when entering the scanning room, and the identity information determination unit 422 may acquire the identity information of the object based on the mark.
  • the mark may be set as a biometric feature, including a fingerprint, a palmprint, a pupil, a pupillary distance, a voiceprint, a facial makeup, a phalanx, the skull, or the like, or any combination thereof.
  • biometric features may be marked in advance and may be stored in a database.
  • the identity information determination unit 422 may match the biometric feature with the biometric features stored in the database to obtain the identity information of the object.
  • the medical device may be pre-started based on the scanning protocol.
  • operation 640 may be performed by the control module 430.
  • control module 430 may pre-start the medical device based on the scanning protocol. In some embodiments, the control module 430 may adjust the rotation speed of the gantry of the medical device (e.g., the medical device 110) according to the reference rotation speed in the scanning protocol based on the scanning protocol. For example, the control module 430 may adjust the rotation speed of the gantry of the medical device (e.g., the medical device 110) to be equal to the reference rotation speed in the scanning protocol. In some embodiments, the control module 430 may adjust one or more parameters associated with anode preheating of the tube of the medical device (e.g., the medical device 110) according to the one or more reference parameters associated with anode preheating in the scanning protocol based on the scanning protocol.
  • control module 430 may adjust the voltage and the current of the tube of the medical device 110 to a reference value corresponding to the voltage of the tube and the current of the tube in the scanning protocol.
  • control module 430 may adjust the positioning state of each component of the scanning device according to the reference positioning state in the scanning protocol based on the scanning protocol. For example, the control module 430 may rotate the medical device 110 to a corresponding rack tilt angle, a pitch, a FOV, or the like.
  • the height of the examination table of the medical device may be adjusted based on the posture information of the object.
  • operation 650 may be performed by the control module 430 (e.g., the examination table control unit 432) .
  • the examination table control unit 432 may determine the target height of the examination table when the object goes to the examination table based on the posture information of the object. It can be understood that an appropriate height of the examination table may facilitate a motion of the object to the examination table.
  • the examination table control unit 432 may calculate a length of a leg of the object based on the posture information of the object, and lower the height of the examination table when the object goes to the examination table to below the length of the leg of the object (e.g., the height of the examination table may be 100 mm below the length of the leg) .
  • the examination table control unit 432 may acquire a height of the cross joint of the object, and further adjust the height of the examination table to below the height of the cross joint to facilitate the object to go to the examination table.
  • the examination table control unit 432 may acquire a height of the wheelchair and lower the height of the examination table to below the height of the wheelchair.
  • the height of the wheelchair may be a standard height (e.g., a uniform height of all wheelchairs in a hospital) .
  • the examination table control unit 432 may directly lower the height of the examination table to below the standard height of the wheelchair.
  • the examination table control unit 432 may determine the height of the wheelchair based on the posture information of the object.
  • the examination table control unit 432 may directly acquire a height of a joint of the object (e.g., a height of the knee joint of the object) , and determine the height of the knee joint as the height of the wheelchair, and further adjust the height of the examination table to be below the height of the knee joint of the object.
  • a height of a joint of the object e.g., a height of the knee joint of the object
  • the examination table control unit 432 may acquire a height of the stretcher and lower the height of the examination table to below the height of the stretcher.
  • the height of the stretcher may be a standard height (e.g., a uniform height of all stretchers in the hospital) .
  • the examination table control unit 432 may directly lower the height of the examination table to below the standard height of the stretcher. In some embodiments, the examination table control unit 432 may determine the height of the stretcher based on the posture information of the object.
  • the examination table control unit 432 may directly acquire the height (e.g., an average value of the leg, a trunk and a head of the object) of the joint of the object, determine the average value of the height of each joint as the stretcher height, and further adjust the height of the examination table to below the height of the stretcher of the object.
  • the height e.g., an average value of the leg, a trunk and a head of the object
  • prompt information may be sent to the object to prompt the object to go to the examination table.
  • a way to prompt the object may include broadcasting, sound prompt, image prompt, text prompt, video prompt, or the like.
  • the prompt information may be output to the object via the terminal 130 with a voice or a text of “Mr. /Ms. XX, the height of the examination table has been adjusted already for you, please go to the examination table for a scan. ”
  • a sound output device in the scanning room may emit a sound such as “beep” to prompt the object to go to the examination table.
  • the prompt information may include a motion distance and/or a motion direction.
  • the prompt information may be: “please move forward two meters before going to the examination table. ”
  • the way to prompt may include others, such as alternating signal lights of different colors (e.g., red, green, etc. ) to prompt the object, which may not be limited in the present disclosure.
  • the subsequent operation may be performed.
  • operation 660 when the object is on the examination table, a plurality of second images of the object on the examination table acquired by the first monitoring device may be obtained.
  • operation 660 may be performed by the acquisition module 410 (e.g., the image acquisition unit 412) .
  • the image acquisition unit 412 may acquire the plurality of second images of the object on the examination table.
  • the image acquisition unit 412 may communicate with an image acquisition device. After a posture on the examination table of the object is determined, the image acquisition unit 412 may acquire the plurality of second images of the object by the image acquisition device.
  • the plurality of second images may be acquired by dividing a continuous video (e.g., obtaining a plurality of still images frame by frame) . More descriptions of dividing the continuous video to obtain the plurality of still images may be found elsewhere in the present disclosure, for example, operation 620, which may not be described herein.
  • actual positioning information of the object may be determined based on the plurality of second images.
  • t operation 670 may be performed by the image analysis module 420 (e.g., the positioning information determination unit 426) .
  • the positioning information determination unit 426 may determine a scanning posture of the object and a positional relationship between the object and the examination table based on the plurality of second images of the object, and further determine the actual positioning information of the object based on the scanning posture and the positional relationship. In some embodiments, the positioning information determination unit 426 may perform one or more operations such as gray-scale change and/or color distortion on the plurality of second images of the object to obtain the contours of the object represented in the plurality of second images, and then determine the scanning posture of the object and the positional relationship between the object and the examination table based on a comparison of the contours.
  • the scanning posture of the object may include a supine posture, a lateral posture, a hand raising, or the like.
  • the positional relationship between the object and the examination table may be measured by a coordinate system.
  • the coordinate system may be established based on the examination table, and the coordinate system may be calibrated for each feature point or contour of the object to obtain corresponding coordinates.
  • the positioning information determination unit 426 may acquire the scanning posture of the object and the positional relationship between the object and the examination table by acquiring 3D contour data of the object.
  • the 3D contour data may be data reflecting a body shape contour of the object.
  • the positioning information determination unit 426 may accurately detect a distance between a point in an image of the object and the camera by a 3D imaging device, thereby acquiring 3D spatial coordinates of the point in a second image of the object, and then obtain the 3D contour data (i.e., a 3D model) of the object by modeling based on the three-dimensional spatial coordinates.
  • the positioning information determination unit 426 may acquire two-dimensional (2D) image data of the object by several 2D imaging devices, and then perform 3D reconstruction based on the 2D image data to obtain the 3D contour data of the object.
  • the 3D contour data of the object acquired by the image acquisition device may include a relative distance and a relative angle between a point in the 3D contour data of the object and the 3D imaging device, or a relative distance and a relative angle between a point in the 3D contour data of the object and the 2D imaging device. Since a position (a distance and an angle) of the 3D imaging device or the 2D imaging device relative to the examination table is determined, a relative position of the object and the examination table may be obtained by processing the above data.
  • the positioning information determination unit 426 may further determine the feature points of the object based on the plurality of second images, and further determine the scanning posture of the object and the positional relationship between the object and the examination table.
  • the coordinates of feature points may be extracted from the plurality of second images by using an algorithm, such as OpenPose, an Hourglass Network, a Rask RCNN, or the like. The more descriptions of acquiring the scanning posture based on the feature points may be found elsewhere in the present disclosure, for example, the operation 620, and may not be described herein.
  • the positioning information determination unit 426 may determine the actual positioning information based on the scanning posture of the object and the positional relationship between the object and the examination table.
  • the actual positioning information may reflect an actual scanning region of the object under a condition of the current scanning posture of the object and the positional relationship between the object and the examination table. It should be understood that the positioning information determination unit 426 may determine a current photographed position (i.e., the actual scanning region) based on the scanning posture of the object and the positional relationship between the object and the examination table.
  • the positioning information determination unit 426 may compare the actual positioning information with predetermined positioning information (or reference positioning information) in the scanning protocol to obtain a matching degree.
  • the predetermined positioning information in the scanning protocol may reflect a target region (e.g., a part in the body of the object corresponding to a nidus) where the object needs to be scanned. For example, when a chest X-ray scan is performed on the object, the chest is a photographed position.
  • the predetermined positioning information in the scanning protocol may be a part in the body that has been determined by a doctor before photographing. And the actual positioning information may reflect the part in the body to be photographed with the position of the object and the scanning posture.
  • the actual positioning information may deviate from the predetermined positioning information because a position of the object may be shifted when the object lying on the examination table.
  • a target position corresponding to the predetermined positioning information may be the chest, but a target position corresponding to the actual positioning information may be the abdomen.
  • the positioning information determination unit 426 may compare the actual positioning information with the predetermined positioning information in the scanning protocol to obtain the matching degree.
  • the matching degree may be represented in a variety of ways, for example, a similarity of positioning information.
  • the matching degree may reflect the similarity between the actual positioning information and the predetermined positioning information in the scanning protocol.
  • the matching degree may be measured by a deviation value of coordinates between two kinds of positioning information and a statistical deviation value of the deviation value of the coordinates (e.g., an average deviation of the coordinates) .
  • the matching degree may reflect a level of the similarity.
  • the level of the similarity may include three levels: 1, 2 and 3. The higher the level of the similarity is, the greater a degree of similarity is.
  • the matching degree may reflect a size of the same region between the actual positioning information and the predetermined positioning information in the scanning protocol.
  • a similarity between two regions corresponding to the actual positioning information and the predetermined positioning information respectively may be 80%, 70%, 35%, or the like. It should be understood that when a degree of similarity between the two regions is 80%, it may represent that a percentage of 80%of the two regions between the actual positioning information and the predetermined positioning information in the scanning protocol are similar.
  • the positioning information determination unit 426 may compare the actual positioning information with the predetermined positioning information in the scanning protocol by using a machine learning model.
  • the machine learning model may be a convolutional neural network.
  • the actual positioning information and the predetermined positioning information in the scanning protocol input into the convolutional neural network may be represented by picture matrixes, and an output of the convolutional neural network may be a similarity between the actual positioning information and the predetermined positioning information.
  • a row of the picture matrix may represent a length of a region corresponding to positioning information (i.e., the actual positioning information or the predetermined positioning information)
  • a column of the picture matrix may represent a width of the region
  • elements of the picture matrix may correspond to pixels (color degrees) of the region.
  • the input of the convolutional neural network may be the picture matrixes corresponding to the actual positioning information and the predetermined positioning information in the scanning protocol
  • the output of the convolutional neural network may be the similarity between the actual positioning information and the predetermined positioning information.
  • a mapping relationship between the actual positioning information and the predetermined positioning information in the scanning protocol may be constructed by the convolutional neural network, and more accurate comparison results may be obtained.
  • the actual positioning information when the actual positioning information does not meet the predetermined condition by comparing the actual positioning information with the predetermined positioning information, the actual positioning of the object on the examination table, that is, the scanning posture of the object and/or the positional relationship between the object and the examination table, may be adjusted to meet the predetermined condition.
  • the object when the actual positioning information does not meet the predetermined condition by comparing the actual positioning information with the predetermined positioning information, the object may be prompted.
  • the prompt information may include voice prompt information and/or a correct positioning image.
  • a prompt content of the prompt information may include adjusting a direction, an angle, a distance, or the like.
  • the monitoring system 100 may generate a prompt message “Mr. /Mrs. Li, please move your right hand away from the chest, and put the right hand on right side of your body! ”
  • the monitoring system 100 may display the correct positioning image to the object via an output device, so that the object may adjust position based on the correct positioning image.
  • operation 690 when the actual positioning information meets a predetermined condition by comparing the actual positioning information with the predetermined positioning information, the object may be sent to the scanning position for scanning.
  • operation 690 may be performed by the control module 430 (e.g., the examination table control unit 432) .
  • a scanning dose of the object may be predetermined based on the scanning protocol.
  • the scanning dose may be stored in the scanning protocol in advance, which may be called directly when the medical device performs a scan on the object.
  • the scanning dose may be determined in real time based on the scanning posture of the object and the actual scanning region, that is, based on the actual positioning information of the object.
  • the relative position of a part to be photographed and the gantry corresponding to the actual positioning information, a thickness, width and height of the part to be photographed may be obtained, thus an appropriate scanning dose may be determined.
  • the scanning dose corresponding to different positioning information may be determined based on statistical data, that is, a correspondence between the positioning information and the scanning dose.
  • the statistical data may be historical diagnosis data from various sources, for example, a scanning image, positioning information, a scanning dose, a target position, patient information, or other data during diagnosis in different regions, different hospitals or different patients.
  • the historical diagnostic data may be analyzed and processed by modeling or using an analysis algorithm with various data, such as statistical analysis, discriminant analysis, etc., to determine scanning doses corresponding to different positioning information. For example, scanning doses used by a plurality of patients of the same age (e.g., 50-55 years old) , the same gender, or the same scanning region during a diagnosis may be counted, thus a scanning dose used by a largest count of patients whose condition is the same with the object may be designated as the scanning dose when a scan is performed on the object.
  • scanning doses used by a plurality of patients of the same age (e.g., 50-55 years old) , the same gender, or the same scanning region during a diagnosis may be counted, thus a scanning dose used by a largest count of patients whose condition is the same with the object may be designated as the scanning dose when a scan is performed on the object.
  • the appropriate scanning dose may be adjusted based on the actual positioning information of the object based on the correspondence between different positioning information and the scanning dose.
  • a trained scanning dose determination model may be used to determine the scanning dose of the object based on the actual positioning information of the object.
  • the scanning dose may include an absolute value, a value within a range, etc.
  • different positioning information may correspond to a minimum and/or maximum of different scanning doses respectively.
  • the scanning dose of the object may be determined based on case information and/or basic information of the object.
  • the case information may be historical diagnosis information of the patient. For example, based on the actual positioning information and/or the basic information of the object, a case record may be queried and matched in the storage device 150 based on a query instruction, and a corresponding scanning dose of the matched case record may be designated as the scanning dose of the object.
  • the determined scanning dose may be store in the scanning protocol for a confirmation by an operator (e.g., a doctor, or a nurse) .
  • the examination table control unit 432 may control the examination table to send the object to the target position for scanning.
  • the running control unit 434 may light an exposure button and wait for the operator to press the exposure button. In some embodiments, the running control unit 434 may scan the object based on an exposure instruction (e.g., an exposure button is pressed by the operator) .
  • a running state of the medical device may be monitored in real time by the monitoring device (e.g., the first monitoring device 160-1 and the second monitoring device 160-2) .
  • the medical device may be stopped to run and/or warning information may be generated based on the abnormal state.
  • a termination instruction may be sent to the medical device and the warning information may be generated. The more description of monitoring the medical device may be found elsewhere in the present disclosure, for example, FIG. 8, and FIG. 9 and the descriptions thereof, which may not be described herein.
  • historical scanning protocols may be searched based on a scanning region corresponding to the actual positioning information of the object to determine whether there is a matched scanning protocol. If there is a scanning protocol in the history scanning protocols that the part to be photographed in the scanning protocol is the same with a part to be photographed corresponding to the actual positioning information and a difference between predetermined posture information in the scanning protocol and actual posture information is within a range of a predetermined threshold, a scanning protocol matching the actual positioning information may be determined in the history scanning protocols. Otherwise, there may be no scanning protocol matching the actual positioning information in the historical scanning protocols.
  • one or more historical scanning protocols may be searched based on a searching keyword (e.g., a chest or a chest X-ray) , and several historical scanning protocols may be selected as candidate scanning protocols.
  • a candidate scanning protocol may be a historical scanning protocol that matches the searching keyword.
  • the posture information of a historical object in the candidate scanning protocol may be compared with the posture information of the object, and the candidate scanning protocol whose comparison result is within a range of a threshold may be regarded as the scanning protocol.
  • the searching keyword may be one or more parameters included in the scanning protocol.
  • the searching keyword may be the positioning information (e.g., standing photographing, lateral photographing, supine photographing, etc. ) of the object in the scanning protocol, and the part to be photographed (e.g., the head, the chest, etc. ) .
  • the positioning information e.g., standing photographing, lateral photographing, supine photographing, etc.
  • the part to be photographed e.g., the head, the chest, etc.
  • the scanning region corresponding to the actual positioning information may be compared with a region corresponding to the historical scanning protocol from many aspects. For example, a height of the object may be compared a height of a historical object in the historical scanning protocol. As another example, a thickness, a width and a height of the part to be photographed of the object may be compared with thickness, a width and a height of the part to be photographed of the historical object. When a comparison result is greater than a threshold, there may be no matching candidate scanning protocol.
  • the thickness of the part to be photographed (e.g., a chest) of the object is 30cm
  • the thickness of the part to be photographed (e.g., a chest) in the candidate scanning protocol is 40cm or 20cm.
  • a difference between the thickness of the part to be photographed of the object and the thickness of the part to be photographed in the candidate scanning protocol is greater than a threshold (e.g., 3cm, 5cm, 7cm, etc. )
  • the candidate scanning protocol may be considered as not matching the actual positioning information.
  • the comparison result is smaller than or equal to the threshold, there may be a matching candidate scanning protocol.
  • the thickness of the part to be photographed (e.g., a chest) of the object is 30cm
  • the thickness of the part to be photographed (e.g., a chest) in the candidate scanning protocol is 35cm or 25cm.
  • a difference between the thickness of the part to be photographed of the object and the thickness of the part to be photographed in the candidate scanning protocol is within a range of the threshold (e.g., 5cm, 7cm, etc. ) , thus the candidate scanning protocol may be considered as matching the actual positioning information.
  • the examination table control unit 432 may control the examination table to return to a position where the object goes to the examination, thus the object may get out of the examination table. In some embodiments, after the scanning is completed, the examination table control unit 432 may control the examination table to adjust to the height of the examination table to the target height.
  • the process 600 may further include the operation 680.
  • a motion trajectory of the examination table from a position where the object goes to the examination table to the target position may be simulated.
  • operation 680 may be performed by the control module 430 (e.g., the examination table control unit 432) .
  • control module 430 may simulate the motion trajectory of the examination table from a position where the object goes to the examination table to the target position based on a predetermined target position, a position where the object goes to the examination table, and a correspondence between the object and the examination table. For example, an interference region corresponding to the examination table may be determined based on the examination table and the motion trajectory from a position where the object goes to the examination table to the target position, and whether an interference involves between the object and one or more components (e.g., the gantry, etc. ) of the medical device may be determined based on the interference region. If the interference does not involve between the object and one or more components, operation 690 may be performed; otherwise, a scanning posture of the object may need to be adjusted to eliminate a risk of the interference.
  • an interference region corresponding to the examination table may be determined based on the examination table and the motion trajectory from a position where the object goes to the examination table to the target position, and whether an interference involves between the object and one or more components (e.g., the
  • the motion trajectory may be planned based on a simulation result, and the examination table may be controlled to move to the target position based on the planned motion trajectory.
  • the planned motion trajectory may include control information such as a motion direction, a motion distance, swing or not and an angle of the examination table.
  • the planned motion trajectory may avoid the interference region to avoid the interference.
  • the motion trajectory of the examination table may be planned again to control a return of the examination table (e.g., the examination table may return from the target position to the position where the object goes to the examination table) .
  • whether the object is suitable for scanning may be determined.
  • mental state information of the object may be determined based on a plurality of third images of the object, and whether the object is suitable for scanning may be determined based on the mental state information.
  • the plurality of third images of the object may be input into a trained mental state recognition model to recognize the mental state information of the object.
  • the mental state information may include rosy cheeks, pathological cheeks, or the like.
  • the plurality of third images may include an image when the object enters the scanning room (e.g., a first image) , an image before the object goes to the examination table, an image when the object is on the examination table (e.g., a second image) , or an image when the object is in the target position.
  • the plurality of third images may be a continuous video of the object during the process of scanning.
  • the plurality of third images of the object may be acquired by the first monitoring device.
  • the scan may be canceled or interrupted.
  • the mental state of the object may be monitored in real time during the process of scanning, and when the mental state of the object is abnormal, the scanning may be terminated in time.
  • the posture information of the object may be acquired by the monitoring device, and the examination table may be automatically lifted and lowered.
  • the medical device may be pre-started by calling the scanning protocol based on the identity information, thus the convenience of scanning may be improved, time of the process of scanning may be reduced, and operations of the process of scanning may be performed rapidly.
  • FIG. 7 is a schematic diagram illustrating an exemplary arrangement of a medical device according to some embodiments of the present disclosure.
  • FIG. 7 shows a scanning room 101 (a ceiling and a side of wall are not shown in order to show an internal structure of the scanning room) , and the medical device 110 (including the examination table 116 and the scanning region 115) may be arranged in the scanning room 101. More descriptions of the medical device 110 may be found elsewhere in the present disclosure, for example, FIG. 1 and the descriptions thereof, which may not be described herein.
  • the monitoring device 160 (e.g., 160-1 or 160-2 shown in FIG. 7) may be arranged on a wall. In some embodiments, the monitoring device 160 may be arranged on the ceiling of the scanning room 101. The monitoring device 160 may be arranged on the ceiling to obtain a broader view, thus avoiding the view being blocked by other institutions or objects.
  • the monitoring device 160 may include only one camera. In this case, the camera may be arranged above the examination table 116. In some embodiments, the monitoring device 160 may include at least two (e.g., two, three, four, five, or six, etc. ) cameras. By setting multiple cameras, the image acquisition field of view of the monitoring device 160 may be effectively increased to avoid the inaccurate image acquisition caused by the blocked area of the field of view of one camera. In some embodiments, two or more cameras may be configured to obtain a 3D image of the object.
  • the two or more cameras may transmit obtained images to the processing device (e.g., the processing device 140) , and the processing device may convert 2D images into the 3D images of the object based on the images obtained by the two or more camera with a way of image mosaic, image coordinate conversion, or the like.
  • the processing device e.g., the processing device 140
  • the processing device may convert 2D images into the 3D images of the object based on the images obtained by the two or more camera with a way of image mosaic, image coordinate conversion, or the like.
  • a count of cameras in the monitoring device 160, the arrangement of cameras, and/or positions of cameras may be determined based on an actual requirement.
  • the arrangement of cameras may include, but be not limited to, array arrangement, ring arrangement, topology arrangement, or the like. Such changes are still within the scope of the present disclosure.
  • an abnormal condition such as keys of the medical device being stuck, or abnormal motion of the medical device may occur when there is no medical staff.
  • a sensor e.g., a force sensor, an infrared sensor, etc.
  • a sensor may be installed on a motion component of the medical device to detect abnormal motion.
  • the abnormal motion may be detected.
  • Some embodiments of the present disclosure may provide a method for monitoring the running state of medical device (for example, process 800 and process 900) , which may monitor the running state of the medical device, thus the abnormal motion of the medical device may be detected in real-time.
  • FIG. 8 is a flowchart illustrating an exemplary process for monitoring a running state of a medical device according to some embodiments of the present disclosure.
  • the process 800 for monitoring the running state of the medical device may be performed by the monitoring system 100 or the processing device 400.
  • the process 800 may be stored in a storage device (e.g., storage device 150) in the form of programs or instructions, and process 800 may be implemented when the monitoring system 100 (e.g., processing device 140) executes the programs or instructions.
  • the operations of the process 800 presented below is illustrative. In some embodiments, the process of the process 800 may be implemented with one or more additional operations not described and/or one or more operations not discussed. In addition, the order of operations of the process 800 shown in FIG. 8 and described below may not intend to be restrictive.
  • a video of a medical device acquired by a first monitoring device arranged in the scanning room may be obtained.
  • operation 810 may be performed by the acquisition module 410 (e.g., the image acquisition unit 412) .
  • the first monitoring device e.g., a camera
  • the first monitoring device may be arranged in the scanning room to monitor the running of the medical device in real time with video and obtain the video of the medical device.
  • the video may be a monitoring video of the medical device obtained in real time by the first monitoring device.
  • the video may include a running performance of the examination table and a gantry of the medical device.
  • the video of the medical device when the object enters the scanning room, the video of the medical device may be obtained by the first monitoring device arranged in the scanning room. In some embodiments, when the object is on the examination table, the video of the medical device may be obtained by the first monitoring device arranged in the scanning room. In some embodiments, in response to determining that actual positioning information meets a predetermined condition based on a plurality of second images of the object, the video of the medical device may be obtained by the first monitoring device set in the scanning room. In some embodiments, when controlling the medical device to send the object to the target position, the video of the medical device may be obtained by the first monitoring device arranged in the scanning room.
  • actual running information of the medical device may be identified based on the video.
  • operation 820 may be performed by the image analysis module 420 (e.g., the running information determination unit 428) .
  • the actual running information may be actual feedback of the medical device on the current operation information.
  • the actual running information and the current operation information may be obtained simultaneously or asynchronously. For example, if there is no time interval between the current operation information and corresponding feedback, the actual running information may be obtained at the same time as the current operation information. If there is a time interval between the current operation information and the feedback, there is also a time interval between a time of obtaining the actual running information and a time of obtaining the current operation information.
  • the current operation information may refer to an input instruction information currently obtained by the medical device, which may be configured to control an operation of the medical device.
  • the current operation information may include pressing a key of “scanning” , selecting "scanning protocol A" , inputting a scanning parameter, or the like.
  • the current operation information may include internal control information and/or key control information.
  • the internal control information of the medical device may be acquired by a controller connected with the medical device.
  • the monitoring system may include a medical device and a console.
  • the console may include a controller and keys as shown in FIG. 10.
  • the controller may be configured to send the internal control information to the medical device, and may receive a scanning result returned by the medical device.
  • the internal control information may be information sent by the controller to the medical device and configured to control the running of the medical device.
  • the current operation information may be obtained based on the internal control information and/or key control information in the controller, thus the adaptability of the method in different scenarios may be improved.
  • the key control information of the medical device may be acquired by a second monitoring device.
  • the key control information may include state information such as pressing or rebounding of a key.
  • Keys may include user interfaces allowing a user to operate the medical device.
  • the second monitoring device 160-2 may be arranged in the operation room 102 that controls the medical device, or may be arranged in the scanning room 101 where the medical device is located.
  • the medical staff may input the internal control information to the medical device via a key on the console.
  • states of different keys on the console may be different.
  • a key monitoring image reflecting a state of pressing or rebounding of the key on the console may be obtained.
  • the state of the key in the key monitoring image may be recognized based on an image segmentation operation, or other image recognition algorithms.
  • the key control information may be obtained.
  • the medical staff may operate the medical device based on a key on the gantry, and a state of the key (e.g., pressing, rebounding, or the key being stuck) on the gantry may be monitored by the second monitoring device in the scanning room.
  • a state of the key e.g., pressing, rebounding, or the key being stuck
  • the state of the key may be recognized by an image recognition algorithm.
  • an image recognition algorithm i.e., model for recognizing the state of the key after in-depth learning and training.
  • the current operation information of the medical device may be obtained at any time from the object entering the scanning room to the object leaving the scanning room. In some embodiments, the current operation information of the medical device may be obtained after starting the medical device.
  • the first monitoring device or the second monitoring device may include at least one of: an image acquisition device, a sensor, or a radar. In some embodiments, both the first monitoring device and the second monitoring device may include an image acquisition device. In some embodiments, the first monitoring device and the second monitoring device may independently include auxiliary detection devices, such as a sensor and/or a radar.
  • the sensor may include an infrared sensor or a sound sensor, and the radar may be a millimeter wave radar.
  • an image acquired by the sensor and/or the radar may be used to replace the unclear image, thus the monitoring may be more accurate.
  • the actual running information may include image information and sound information. In some embodiments, the actual running information of the medical device may be determined by identifying the image information and sound information in the video.
  • the image information in the video may be recognized by the image recognition algorithm
  • the sound information in the video may be recognized by the voice recognition algorithm.
  • the image recognition algorithm and the voice recognition algorithm may be deep-learning algorithms. For example, during training, a running image/of the medical device for training and a running image marked with the actual running information may be designated as a training set, and in-depth model training may be performed based on the training set to obtain the image recognition algorithm that used to recognize the actual running information. As another example, during training, sound information of the medical device for training and sound information marked with the actual running information may be designated as a training set, and in-depth model training may be performed based on the training set to obtain the sound recognition algorithm that used to recognize the actual running information.
  • the medical device may generate different sounds from a sound generated in normal motion, so the abnormal state of the medical device may be determined based on the sound information.
  • the accuracy of recognizing the actual running information may be improved by identifying the image information and sound information of the medical device in the video.
  • the running state of the medical device may be controlled based on the actual running information and the expected running information.
  • operation 830 may be performed by the control module 430 (e.g., the running control unit 434) .
  • the expected running information may refer to a motion corresponding to the current operation information that the medical device should perform in a condition that the medical device is not in an abnormal state.
  • the expected running information may include a tilt of the gantry, a motion of the examination table, or the like.
  • the excepted operation information may include a standard operation process.
  • the standard operation process may refer to operations to be performed and a sequence of each operation in the process of scanning the object, for example, inputting patient information->>moving the examination table->>selecting the scanning protocol->>determining parameters of scanning->>starting to scan->>ending the scan->>processing an image, or the like.
  • the expected running information of the corresponding medical device may be different.
  • an instruction of adjusting the height of the examination table need to be executed, such as the expected running information of the medical device is moving the examination table up or down. If the actual running information is inconsistent with the expected running information at a corresponding stage, an operation of the medical staff may violate the standard operation process or the medical device may be in an abnormal state.
  • the actual running information of the medical device may be compared with the expected running information, and the operation state of the medical device may be obtained after comparing the actual running information and the expected running information.
  • the running state of the medical device may be configured to evaluate whether the medical device is in an abnormal state, indicating whether there is an abnormal situation in running of medical device.
  • the running state of a medical device may include a normal state or an abnormal state.
  • the medical device may be determined in a normal state.
  • the medical device may maintain the current running state, and the first monitoring device may continue to monitor the medical device.
  • the actual running information is inconsistent with the expected running information, the medical device may be determined in an abnormal state.
  • the medical device when the expected running information is inconsistent with the actual running information, the medical device may be determined in an abnormal state. In some embodiments, if the expected running information determined based on the current operation information is inconsistent with the actual running information, the medical device may be determined in an abnormal state, and the current operation information may include internal control information and/or key control information.
  • the actual running information of the medical device may be compared with the expected running information corresponding to the key being stuck to determine whether the medical device is in an abnormal state.
  • the medical device may be considered to be in an abnormal state when the key is stuck or there is no person to operate but the medical device is still running.
  • the expected running information corresponding to the key being stuck may be consistent with the expected running information corresponding to the key being rebound. Specifically, when the medical device is not in an abnormal state, the key may rebound normally after being pressed. At this time, the medical device may have a corresponding expected running information. Therefore, if the key cannot rebound normally due to the key being stuck, the medical device may not operate with the expected running information.
  • a special situation of the key being stuck may be considered, and the corresponding expected running information may be set for the key being stuck to meet requirements of different scenarios.
  • other excepted operation information may be set for the key being stuck based on the actual requirements. For example, when the key is stuck, the medical device may run based on an existing running state, or stop running and remain stationary.
  • the medical device may have abnormal motion caused by a component failure, a software error, or the like monitoring may be performed based on the internal control information, which is a software control instruction received inside the controller.
  • the controller may compare the monitoring image acquired by the first monitoring device with the internal control information of the medical device. If the actual running information obtained from the monitoring image conflicts with the internal control information of the medical device, the medical device may be in an abnormal state.
  • the key being stuck may include two conditions as follows: 1) The key may be stuck when a medical staff is not operating the medical device; 2) after the medical staff actively presses the key, the key may not be rebounded. Both of the two conditions may cause an abnormal state of the medical device.
  • the first condition the actual running information of the medical device may be obtained by the first monitoring device. If the medical device moves without touching the key artificially, the key may be stuck.
  • the second condition the monitoring image of the key may be obtained by the second monitoring device, and then the key control information may be obtained from the monitoring image of the key to determine whether the key is rebounded. If the key is not rebounded, the key may be stuck.
  • the current operation information may be determined based on the internal control information or key control information. If the internal control information and key control information are obtained at the same time, and current operation information obtained by the internal control information and key control information respectively are inconsistent, one of the corresponding current operation information may be selected based on a predetermined priority for judgment.
  • the excepted running information may be obtained based on the internal control information and/or key control information in some embodiments of the present disclosure. Then, the excepted running information may be compared with the actual running information to judge the running state of the medical device, thus the accuracy of judging the running state of the medical device may be improved.
  • the current operation information of the medical device may be compared with the excepted running information to determine whether the medical device is in an abnormal state.
  • the current operation information and previous operation information may be compared with the excepted running information corresponding to previous process, and compared with the excepted running information corresponding to current process to determine whether the medical device is in an abnormal state. For example, if the current operation information is determining a scanning dose, and corresponding excepted running information is determining a scanning protocol, thus the medical device may be in an abnormal state.
  • the operation of the medical device in response to determining that the medical device is in an abnormal state, the operation of the medical device may be stopped, and warning information may be generated based on an abnormal state to remind the medical staff that the medical device has been stopped urgently. Thus, more serious accidents may be avoided and losses may be reduced.
  • a termination instruction may be sent to the medical device by a controller connected with the medical device to stop the medical device.
  • the warning information may be generated based on the abnormal state and sent to a communication device of the medical staff, or an audible and visual alarm may be performed.
  • the actual running information of the medical device may be obtained in real time based on the first monitoring device in some embodiments of the present disclosure, and the actual running information may be compared with the expected information to obtain real-time running state of the medical device, the abnormal motion may be detected at the moment of the medical device is in the abnormal state, thus the detection efficiency and detection accuracy of the abnormal motion of the medical device may be improved.
  • FIG. 9 is a flowchart illustrating an exemplary process for obtaining expected running information of a medical device according to some embodiments of the present disclosure.
  • a process 900 may be performed by the monitoring system 100 or processing device 400.
  • the process 900 may be stored in a storage device (e.g., the storage device 150) in the form of programs or instructions.
  • the process 900 may be implemented when the monitoring system 100 (e.g., the terminal 130) executes the programs or instructions.
  • the operations of the process 900 presented below is illustrative.
  • a process of the process 900 may be implemented with one or more additional operations not described and/or one or more operations not discussed.
  • the order of operations of the process 900 shown in FIG. 9 and described below is not intended to be restrictive.
  • internal control information of the medical device may be acquired by a controller connected with the medical device and designated as the current operation information.
  • key control information of the medical device may be obtained by the second monitoring device and designated as the current operation information. More descriptions of obtaining the current operation information may be found elsewhere in the present disclosure, for example, FIG. 8 and the descriptions thereof, which may not be described herein.
  • 920 a predetermined correspondence between the current operation information and the excepted running information may be obtained.
  • the medical device may have a corresponding feedback, (i.e., the running information) , and the correspondence between the operation information and the running information may be stored in the controller in advance.
  • a corresponding feedback i.e., the running information
  • Scans for the same part or the same type of scans may correspond to the same standard operation process.
  • a scan for the chest and a scan for the abdomen may correspond to different standard operation processes.
  • different stages may correspond to different operation information, and correspondingly, may correspond to different excepted running information.
  • the examination table Before monitoring the running state of medical device, correspondence between all operation information and running information may be obtained. For example, under what kind of internal control information and key control information, the examination table may need to move forward accordingly. Under what kind of internal control information and key control information, the examination table needs to go back. Under what kind of key control information, the medical device needs to stop running.
  • the predetermined correspondence between the current operation information and the excepted running information may be obtained from a storage device (e.g., the storage device 150) .
  • excepted running information may be obtained based on the predetermined correspondence and the current operation information.
  • operation information consistent with the current operation information may be found in the predetermined correspondence, and then corresponding running information may be found as the excepted running information based on the predetermined correspondence.
  • determining the excepted running information based on the predetermined correspondence may improve the accuracy of identifying the excepted running information.
  • FIG. 10 is a schematic diagram illustrating an exemplary system for monitoring a medical device according to some embodiments of the present disclosure.
  • a monitoring system 1000 may include the medical device 110 and the console 1020.
  • the console may further include a controller (e.g., the processing device 140) and a key (e.g., the terminal 130) .
  • the medical device 110 may be arranged in the scanning room 101, and the console 1020 may be arranged in the operation room 102.
  • the first monitoring device 160-1 may be arranged in the scanning room 101 to monitor the medical device 110
  • the second monitoring device 160-2 may be arranged in the operation room 102 or the scanning room 101 to monitor one or more keys of the console 1020 and one or more keys on the gantry of the medical device 110.
  • the controller may be composed of one or more central processors, which may be configured to receive signals such as the actual running information of the medical device 110 acquired by the first monitoring device 160-1 and the key control information acquired by the second monitoring device 160-2.
  • the controller may be configured to receive the internal control information of the medical device 110.
  • the one or more keys may include a virtual touch-screen key and/or a physical key.
  • a count of the first monitoring device 160-1 and a count of the second monitoring device 160-2 may be determined based on actual requirements. It should be noted that a position and the count of the first monitoring device 160-1 and t a position and the count of the second monitoring device 160-2 in FIG. 10 are merely for illustration and not be limited.
  • the key control information may include whether there is a medical staff operating the console 1020, a CTBOX, a control panel on the gantry of the CT system, or the like.
  • the CTBOX is a control box of the CT system.
  • the controller may compare the actual running information in the scanning room 101 acquired by the first monitoring device 160-1 with the internal control information to determine whether a motion of the CT system is triggered artificially, purposefully and consciously.
  • the CT system may be in an abnormal state, and the controller may terminate the abnormal motion of the CT system, and prompt a staff that the abnormal motion (e.g., the key being stuck) exists based on alarms, or other ways.
  • the image information and sound information of the operation room 102 and the scanning room 101 may be analyzed.
  • the image information may refer to the actual running information acquired by the first monitoring device 160-1 or the current operation information acquired by the second monitoring device 160-2.
  • the sound information may be a sound (e.g., a sound of the examination table hitting on the gantry) of the CT system in the abnormal state in the scanning room 101.
  • the image information and the sound information may be obtained at different times.
  • the controller may fuse the image information in the operation room and the image information scanning room at the same time to make a more accurate comparison.
  • the controller may fuse the image information, the sound information and data information acquired by a detection device, such as a line sensor, a radar, or the like.
  • the abnormal motion of the medical device 110 may be detected based on the first monitoring device 160-1 and the second monitoring device 160-2 in the embodiment, and the abnormal motion may be detected and warned immediately when the medical device is in an abnormal state. At the same time, when the medical device is in an abnormal state, a motion of the medical device may be stopped immediately. Thus, the risks may be reduced. Thus, a real-time running performance of the medical device may be monitored accurately, and the abnormal state of the medical device may be quickly detected and determined, thus the abnormal state may be timely terminated to avoid harm and the safety of the medical device may be ensured.
  • a count of cameras, an arrangement of the cameras and/or a location of cameras in the first monitoring device 160-1 and the second monitoring device 160-2 may be determined based on actual requirements.
  • the arrangement of cameras may include, but be not limited to: array arrangement, ring arrangement, topology arrangement, or the like. These changes are still within the scope of the present disclosure.
  • the monitoring device may be configured to acquire the posture information of the object, and the height of the examination table may be adjusted based on the posture information, thus the convenience and efficiency of medical scanning may be improved; (2) a pre-start operation of the medical device may be performed based on a corresponding scanning protocol of the identity information of the object, thus the scanning time of the scanning may be reduced, and the scanning may be performed efficiently; (3) an actual positioning of the object may be identified based on the second image acquired by the monitoring device and the positioning of the object may be guided based on the actual positioning, thus the object may be helped to be in an appropriate positioning state, and the scanning efficiency may be improved; (4) by simulating a motion trajectory of the examination table from a position where the object goes to the examination table to the target position, an interference involved between the object and the medical device may be avoided and the safety of the object may be improved; (5) by acquiring the mental state information of the object by the monitoring device and judging whether it is suitable for scanning based on the mental state information, a condition that
  • the numbers expressing quantities of ingredients, properties, and so forth, used to describe and claim certain embodiments of the application are to be understood as being modified in some instances by the term “about, ” “approximate, ” or “substantially. ”
  • “about, ” “approximate, ” or “substantially” may indicate ⁇ 20%variation of the value it describes, unless otherwise stated.
  • the numerical parameters set forth in the written description and attached claims are approximations that may vary depending upon the desired properties sought to be obtained by a particular embodiment.
  • the numerical parameters should be construed in light of the number of reported significant digits and by applying ordinary rounding techniques. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of some embodiments of the application are approximations, the numerical values set forth in the specific examples are reported as precisely as practicable.

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  • Health & Medical Sciences (AREA)
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  • High Energy & Nuclear Physics (AREA)
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  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
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Abstract

Dispositif médical (110), procédé et système (100) de surveillance du dispositif médical (110). Le procédé peut consister à obtenir une pluralité de premières images d'une salle de balayage acquises par un premier dispositif de surveillance (160) agencé dans la salle de balayage ; à obtenir un résultat d'analyse par analyse de la pluralité de premières images ; et à commander le dispositif médical (110) sur la base du résultat d'analyse, le dispositif médical (110) comprenant une table d'examen (116). Un mode de commande du dispositif médical (110) peut comprendre la commande du dispositif médical (110) pour ajuster une hauteur de la table d'examen (116), et/ou la commande du dispositif médical (110) pour envoyer un objet à une position cible, et/ou la commande d'un état de fonctionnement du dispositif médical (110).
PCT/CN2022/117823 2021-09-08 2022-09-08 Dispositifs médicaux, procédés et systèmes de surveillance des dispositifs médicaux WO2023036243A1 (fr)

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CN202111052132.5A CN113647967A (zh) 2021-09-08 2021-09-08 一种医学扫描设备的控制方法、装置及***
CN202111087938.8A CN113796875A (zh) 2021-09-16 2021-09-16 医学扫描设备运动状态监控方法、***和电子装置
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